Data Science Manager (Data Methods)

Job Description

We’re reinventing the market research industry. Let’s reinvent it together. At Numerator, we believe tomorrow’s success starts with today’s market intelligence. We empower the world’s leading brands and retailers with unmatched insights into consumer behavior and the influencers that drive it. The Data Methods Data Science Lead will be expected to independently define and lead all analyses and develop solutions to support key innovation initiatives and methodology development, The individual will have a relatively advanced understanding of our E2E processes, and be able to relatively independently work on identifying areas for improvement, assessing what enhancements should be made and working with other teams to implement these changes. There will be a strong focus on using panel data across our services working via our dedicated Data Processing Platform on Databricks. Main Duties And Responsibilities Data Methods / Data Science Primary Role: Able to drive independently key initiatives and projects related to Data Methods Project Plans: Outline project scope, objectives, timelines and milestones. Data Collection / Preparation: Management of data (e.g. cleaning, preprocessing). Exploratory Data Analysis: Conduct feasibility studies potential solutions / lead prototyping. Model Development: Building and validating models using various data science algorithms. Model Deployment: Designing requirements / testing / deploying models in production. Reporting and Documentation: Methods used, findings and recommendations. Training and Support: Training and providing deployment support. Project Review and Evaluation: Conducting reviews of project outcomes Able to form views on how new processes ought to be constructed. Co-ordinate work with On-Shore Methods Manager / Leads Able to contribute both to BAU enhancements and to work under the umbrella of a project. Understanding the wider business Develops a basic understanding of the Operations functions Develop an understanding of the Commercial usage of our data Develop a broader understanding of our direct competitors Training & Development Take ownership for self-development and where available participate in structured training. Gains proficiency in all relevant databases, data interrogation and reporting tools (for example Databricks, SQL, Python , Excel, etc.) Communication & Collaboration Ability to collaborate across key stakeholders in operations, technology and product teams Ability to collaborate and communicate with stakeholders upwards and with team members Be able to communicate in an appropriate manner (e.g. verbally, presenting or creating a PowerPoint, Word document, email) Adhering to deadlines and escalating where there is a risk of delays Demonstrate and role model best practise and techniques including positive communication style. Displays a proactive attitude when working both within and outside of the team. Demonstrates clear, direct and to the point communication at Data Methods team meetings Issue Management and Best Practice Proactive identification and root cause analysis of Data Methods issues and development of best practice solutions to improve the underlying methodology and processes. Support regular methodology review meetings with On-Shore Manager and Leads to establish priorities and future requirements. Knowledge sharing through the team, in either team meeting or day-to-day with the wider Data Methods team Able to think through complex processes and to how to construct and improve them, considering in detail the positive and negative implications of different approaches and how best to test and assess them. Resource management Organising workload efficiently Adhering to schedules Escalating any risks to deadlines and capacity challenges What You'll Bring to Numerator Education & Experience Bachelors, Masters, Doctorate Degree 3+ years experience Knowledge Domain expertise in 3-5 of: Data collection methods Fraud detection methods Data cleaning methods Demographics methods Sampling methods Bias methods Eligibility methods Weighting methods Data aggregation methods Outlier methods Statistical modelling Metrics / KPI methods Tools Python [or R] (advanced - ability to independently script end-to-end functioning programmes) Databricks (intermediate) SQL (intermediate) Azure Dev Ops (basic) Git (basic) Excel (advanced) Power BI (intermediate) Passion and Drive Passionate about data quality, integrity and best practices Passionate about delivering high quality data to clients on schedule Communication Ability to communicate complex technical concepts to stakeholders in simple language Good English communication, presentation, interpersonal and writing skills Good listening skills Good online, virtual, and in-person collaboration skills Comfortable presenting panel and data methods to external audiences (internal) Show more Show less